HFBTHO-AD: Differentiation of a nuclear energy density functional code

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Hascoët, Laurent, Menickelly, Matt, Narayanan, Sri Hari Krishna, O'Neal, Jared, Schunck, Nicolas, Wild, Stefan M.
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917085278371840
author Hascoët, Laurent
Menickelly, Matt
Narayanan, Sri Hari Krishna
O'Neal, Jared
Schunck, Nicolas
Wild, Stefan M.
author_facet Hascoët, Laurent
Menickelly, Matt
Narayanan, Sri Hari Krishna
O'Neal, Jared
Schunck, Nicolas
Wild, Stefan M.
contents The HFBTHO code implements a nuclear energy density functional solver to model the structure of atomic nuclei. HFBTHO has previously been used to calibrate energy functionals and perform sensitivity analysis by using derivative-free methods. To enable derivative-based optimization and uncertainty quantification approaches, we must compute the derivatives of HFBTHO outputs with respect to the parameters of the energy functional, which are a subset of all input parameters of the code. We use the algorithmic/automatic differentiation (AD) tool Tapenade to differentiate HFBTHO. We compare the derivatives obtained using AD against finite-difference approximation and examine the performance of the derivative computation.
format Preprint
id arxiv_https___arxiv_org_abs_2508_11910
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle HFBTHO-AD: Differentiation of a nuclear energy density functional code
Hascoët, Laurent
Menickelly, Matt
Narayanan, Sri Hari Krishna
O'Neal, Jared
Schunck, Nicolas
Wild, Stefan M.
Nuclear Theory
The HFBTHO code implements a nuclear energy density functional solver to model the structure of atomic nuclei. HFBTHO has previously been used to calibrate energy functionals and perform sensitivity analysis by using derivative-free methods. To enable derivative-based optimization and uncertainty quantification approaches, we must compute the derivatives of HFBTHO outputs with respect to the parameters of the energy functional, which are a subset of all input parameters of the code. We use the algorithmic/automatic differentiation (AD) tool Tapenade to differentiate HFBTHO. We compare the derivatives obtained using AD against finite-difference approximation and examine the performance of the derivative computation.
title HFBTHO-AD: Differentiation of a nuclear energy density functional code
topic Nuclear Theory
url https://arxiv.org/abs/2508.11910